Alice in Wonderland: The effects of body size and movement on children’s size perception and body representation in virtual reality
Bibliographic record
Abstract
Previous work shows that in adults, illusory embodiment of a virtual avatar can be induced using congruent visuomotor cues. Furthermore, embodying different-sized avatars influences adults' perception of their environment's size. This study (N = 92) investigated whether children are also susceptible to such embodiment and size illusions. Adults and 5-year-old children viewed a first-person perspective of different-sized avatars moving either congruently or incongruently with their own body. Participants rated their feelings of embodiment over the avatar and also estimated the sizes of their body and objects in the environment. Unlike adults, children embodied the avatar regardless of visuomotor congruency. Both adults and children freely embodied different-sized avatars, and this affected their size perception in the surrounding virtual environment; they felt that objects were larger in a small body and vice versa in a large body. In addition, children felt that their body had grown in the large body condition. These findings have important implications for both our theoretical understanding of own-body representation, and our knowledge of perception in virtual environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".